CN108663988B - Intelligent monitoring system of numerical control machine tool based on Internet of things - Google Patents

Intelligent monitoring system of numerical control machine tool based on Internet of things Download PDF

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CN108663988B
CN108663988B CN201810548467.8A CN201810548467A CN108663988B CN 108663988 B CN108663988 B CN 108663988B CN 201810548467 A CN201810548467 A CN 201810548467A CN 108663988 B CN108663988 B CN 108663988B
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CN108663988A (en
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黄信文
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Siling robot technology (Harbin) Co.,Ltd.
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Harbin Modi Science And Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
    • G05B19/4065—Monitoring tool breakage, life or condition
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/37—Measurements
    • G05B2219/37616—Use same monitoring tools to monitor tool and workpiece

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Abstract

The invention provides an intelligent monitoring system of a numerical control machine tool based on the Internet of things, which comprises a plurality of sensors arranged on the numerical control machine tool, a data collecting subsystem used for collecting state information data of the numerical control machine tool through the sensors, a data processing subsystem used for preprocessing the state information data collected by the data collecting subsystem, an Internet of things server used for storing the preprocessed state information data and a user terminal used for displaying the state information data; the data collection subsystem is respectively connected with the sensor and the data processing subsystem, and the data processing subsystem and the user terminal are respectively connected with the Internet of things server; the data processing subsystem comprises a data anomaly detection module and a data fusion processing module, the data anomaly detection module is used for carrying out anomaly detection on the state information data and repairing the detected abnormal data, and the data fusion processing module is used for carrying out fusion processing on the state information data.

Description

Intelligent monitoring system of numerical control machine tool based on Internet of things
Technical Field
The invention relates to the technical field of machine tool monitoring, in particular to an intelligent monitoring system of a numerical control machine tool based on the Internet of things.
Background
The numerical control machine tool is an automatic machine tool provided with a program control system. The machine tool has the characteristics of high machining precision, stable machining quality, high flexibility, high productivity, high automation degree of the machine tool, capability of reducing labor intensity and the like. With the development of industry, people have higher and higher requirements on the use of numerical control machines. However, the cost of the relative machine tool equipment is relatively high, and with the increase of the machine tool equipment, the aspects of the use efficiency, the running state monitoring, the machine tool fault prejudgment, the machine tool resource allocation and the like of the machine tool equipment are greatly challenged, the existing machine tool monitoring generally analyzes and monitors the machine tool based on collected data recorded manually, and when a plurality of users need to know the state information of different machine tools, the real-time performance of the machine tool monitoring cannot meet the rapid development requirements of multi-party enterprises.
Disclosure of Invention
Aiming at the problems, the invention provides an intelligent monitoring system of a numerical control machine tool based on the Internet of things.
The purpose of the invention is realized by adopting the following technical scheme:
the system comprises a plurality of sensors arranged on the numerical control machine, a data collection subsystem used for collecting state information data of the numerical control machine through the sensors, a data processing subsystem used for preprocessing the state information data collected by the data collection subsystem, an Internet of things server used for storing the preprocessed state information data and a user terminal used for displaying the state information data; the data collection subsystem is respectively connected with the sensor and the data processing subsystem, and the data processing subsystem and the user terminal are respectively connected with the Internet of things server; the data processing subsystem comprises a data anomaly detection module and a data fusion processing module, the data anomaly detection module is used for carrying out anomaly detection on the state information data and repairing the detected abnormal data, and the data fusion processing module is used for carrying out fusion processing on the state information data.
Preferably, the data collection subsystem comprises a signal adapter for converting sensor signals into corresponding status information data, the signal adapter being connected to the sensor.
Further, the data collection subsystem further comprises a controller for controlling the acquisition frequency, the controller being connected to the sensor.
The user terminal comprises any one or more of an LED display screen, an LCD display screen, a smart phone, a notebook computer and a desktop computer.
The sensor comprises any one or more of a temperature sensor, a vibration sensor, a liquid level sensor, a displacement sensor, a current sensor and a Hall sensor.
The invention has the beneficial effects that: the invention can facilitate the different user terminals to check the state information data in time, so that the user can know the state information of the numerical control machine tool in time, thereby carrying out proper selection or processing according to the state information of the numerical control machine tool, improving the utilization rate of the numerical control machine tool, meeting the requirement of people on knowing the state information of the numerical control machine tool in real time, and early warning the numerical control machine tool which is likely to have faults in advance, so that the working personnel or maintenance personnel can carry out corresponding processing conveniently, and the loss caused by the machine tool faults is reduced.
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The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a block diagram schematically illustrating the construction of a monitoring system of a numerical control machine tool according to an exemplary embodiment of the present invention;
FIG. 2 is a block diagram illustrating the structure of a data processing subsystem in accordance with an exemplary embodiment of the present invention.
Reference numerals:
the system comprises a sensor 1, a data collection subsystem 2, a data processing subsystem 3, an Internet of things server 4, a user terminal 5, a data anomaly detection module 10 and a data fusion processing module 20.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1, an embodiment of the present invention provides an intelligent monitoring system for a numerically-controlled machine tool based on the internet of things, which includes a plurality of sensors 1 disposed on the numerically-controlled machine tool, a data collection subsystem 2 for collecting status information data of the numerically-controlled machine tool through the sensors, a data processing subsystem 3 for preprocessing the status information data collected by the data collection subsystem 2, an internet of things server 4 for storing the preprocessed status information data, and a user terminal 5 for displaying the status information data; the data collection subsystem 2 is respectively connected with the sensor 1 and the data processing subsystem 3, and the data processing subsystem 3 and the user terminal 5 are respectively connected with the internet of things server 4.
In one embodiment, the data collection subsystem 2 includes a signal adapter for converting the signals of the sensors 1 into corresponding status information data, the signal adapter being connected to the sensors 1.
Further, the data collection subsystem 2 further comprises a controller for controlling the acquisition frequency, the controller being connected to the sensor.
The user terminal 5 comprises any one or more of an LED display screen, an LCD display screen, a smart phone, a notebook computer and a desktop computer.
The sensor 1 comprises any one or more of a temperature sensor, a vibration sensor, a liquid level sensor, a displacement sensor, a current sensor and a Hall sensor.
The numerical control machine monitoring system designed by the embodiment of the invention can facilitate different user terminals 5 to check the state information data in time, so that a user can know the state information of the numerical control machine in time, and therefore, proper selection or processing can be carried out according to the state information of the numerical control machine, the utilization rate of the numerical control machine is improved, the requirement of people on knowing the state information of the numerical control machine in real time is met, the numerical control machine with possible faults can be pre-warned in advance, so that the corresponding processing can be conveniently carried out by working personnel or maintenance personnel, and the loss caused by the machine faults is reduced.
In one implementation, as shown in fig. 2, the data processing subsystem 3 includes a data anomaly detection module 10 and a data fusion processing module 20, the data anomaly detection module 10 is configured to perform anomaly detection on the state information data and repair the detected anomalous data, and the data fusion processing module 20 is configured to perform fusion processing on the state information data.
In one embodiment, when the sensors 1 are deployed, a monitoring area for monitoring the numerical control machine tool is partitioned, different types of sensors 1 are deployed in each partition, the number of the same type of sensors 1 deployed in different partitions is the same, and data sampling time intervals of the sensors 1 are set to be consistent.
The deployment mode of the sensor 1 of the above embodiment can facilitate subsequent data processing.
In one embodiment, the data anomaly detection module 10 performs anomaly detection on the state information data, specifically including:
(1) setting the width N of the data analysis time window, scanning the status information data sent by the data transceiver module 10 in real time by using the data analysis time window, and scanning a status information data yiIf the normal range exceeds the preset normal range, performing (2); otherwise, judging the state information data to be normal;
(2) calculating the number of scan status informationAccording to yiThe mean, standard deviation and median of the state information data within the time window of data analysis;
(3) if the status information data yiIf the following condition is satisfied, the state information data y is determinediIs normal; otherwise, judging the state information data yiFor anomalous data:
Figure GDA0002244409820000032
in the formula (I), the compound is shown in the specification,
Figure GDA0002244409820000031
for scanning the status information data yiU is the scan state information data yiThe standard deviation of the state information data within the time window is analyzed.
The abnormal condition of the state information data is two kinds, namely, the abnormal condition is caused by the influence of factors such as the fault of the sensor 1, the fault of the data acquisition terminal, the bad environment and the like, and the abnormal condition is caused by the problem of the working parameters of the numerical control machine. During monitoring, abnormal data acquired due to the fact that working parameters of the numerical control machine tool are in a problem are usually important data and need to be reserved for further data analysis, and abnormal data caused by hardware faults and the like are not real data and need to be repaired.
In view of the above situation, the present embodiment innovatively provides a mechanism for detecting abnormal data, which detects status information data in a window scanning manner, and can more quickly complete the abnormal identification of status information data compared with a manner of detecting status information data one by one, because only the status information data exceeding a preset normal range is detected abnormally; by analyzing the relationship between the state information data beyond the preset normal range and the state information data in the data analysis time window, the actual reason why the state information data exceeds the preset normal range can be judged, and whether the state information data is real data or not is determined.
In an embodiment, the data anomaly detection module 10 repairs the detected anomalous data, specifically including: if the status information data y is judgediReplacing the abnormal data with a repair value for the abnormal data, and marking;
wherein, the calculation formula of the set restoration value is as follows:
Figure GDA0002244409820000041
wherein y' represents the repair value, max is the maximum value of the state information data in the current data analysis time window, min is the minimum value of the state information data in the current data analysis time window, ymedThe median value of the state information data within the time window is analyzed for the current data.
When the data anomaly detection module 10 repairs the detected anomalous data, the repair value of the replaced anomalous data is obtained according to the set calculation formula of the repair value, wherein the calculation formula calculates the repair value of the replaced anomalous data by combining the mean value and the median value of the state information data in the data analysis time window.
In an embodiment, the data fusion processing module 20 performs fusion processing on the state information data, specifically: the sensors 1 belonging to the same type and the same partition are regarded as the same fusion component unit, and the state information data belonging to the same fusion component unit is subjected to fusion processing in units of time periods.
The fusion processing is performed on the state information data belonging to the same fusion component unit by taking a time period as a unit, and the fusion processing specifically comprises the following steps:
(1) taking the state information data belonging to the same fusion composition unit as basic data participating in fusion, calculating the average value of the basic data of each time period corresponding to each sensor 1, and calculating the quantity of the marked state information data in each time period corresponding to each sensor 1;
(2) extracting the average value of the basic data of each sensor 1 in the same time period as the data to be fused to form a data sequence to be fused
Figure GDA0002244409820000042
k is the number of the extracted average values of the basic data, and the noise variance of the sensor 1 corresponding to each data to be fused is obtained;
(3) calculating the reliability of the sensor 1 corresponding to each data to be fused:
Figure GDA0002244409820000043
in the formula, EiIndicating the sensor 1, E corresponding to the ith data to be fusedlRepresents the sensor 1 corresponding to the ith data to be fused,
Figure GDA0002244409820000044
indicating the sensor 1EiThe degree of reliability of the optical waveguide is high,
Figure GDA0002244409820000045
is a sensor 1EiThe variance of the noise of (a) is,
Figure GDA0002244409820000046
is a sensor 1ElThe noise variance of (2);
Figure GDA0002244409820000047
in order to ensure that the sensor 1E is in the time period corresponding to the ith data to be fusediThe number of marked state information data in the collected state information data;
Figure GDA0002244409820000048
in order to ensure that the sensor 1E is in the time period corresponding to the ith data to be fusediThe number of marked state information data in the collected state information data;
(4) the data sequence to be fused is treated according to the following formula
Figure GDA0002244409820000051
Carrying out fusion treatment:
Figure GDA0002244409820000052
in the formula, y represents the fusion result.
In the embodiment, the characteristics of multi-source state information data are considered, and a data fusion processing mechanism is innovatively provided, which considers the problem of time-space matching of data and performs fusion processing on state information data belonging to the same fusion component unit by taking a time period as a unit, so that fusion data of the same region in the same period can be obtained. In this embodiment, when fusion processing is performed on data to be fused, the problem of reliability of the sensor 1 to which the data to be fused belongs is considered, the reliability of the sensor 1 is used as the weight of the data to be fused, and a fusion value is calculated based on a weighted average method, so that the calculated fusion value can be closer to the actual situation, and the data accuracy is higher.
In this embodiment, a calculation formula of the reliability of the sensor 1 is designed based on two aspects of the number of times that the sensor 1 acquires abnormal data and the noise variance, and the performance of the sensor 1 in the aspect of data acquisition precision can be objectively measured, so that a good foundation is laid for accurately calculating a fusion value, and the precision of the intelligent monitoring system of the numerically-controlled machine tool based on the internet of things in the aspects of data acquisition and data processing is further improved.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, the modules may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (6)

1. The intelligent monitoring system of the numerical control machine tool based on the Internet of things is characterized by comprising a plurality of sensors arranged on the numerical control machine tool, a data collecting subsystem used for collecting state information data of the numerical control machine tool through the sensors, a data processing subsystem used for preprocessing the state information data collected by the data collecting subsystem, an Internet of things server used for storing the preprocessed state information data and a user terminal used for displaying the state information data; the data collection subsystem is respectively connected with the sensor and the data processing subsystem, and the data processing subsystem and the user terminal are respectively connected with the Internet of things server; the data processing subsystem comprises a data anomaly detection module and a data fusion processing module, the data anomaly detection module is used for carrying out anomaly detection on the state information data and repairing the detected abnormal data, and the data fusion processing module is used for carrying out fusion processing on the state information data; the data anomaly detection module performs anomaly detection on the state information data, and specifically comprises:
(1) setting the width N of a data analysis time window, scanning the state information data sent by the data transceiver module in real time by adopting the data analysis time window, and if the state information data y is scannediIf the normal range exceeds the preset normal range, performing (2); otherwise, judging the state information data to be normal;
(2) calculating scan status information data yiThe mean, standard deviation and median of the state information data within the time window of data analysis;
(3) if the status information data yiIf the following condition is satisfied, the state information data y is determinediIs normal; otherwise, judging the state information data yiFor anomalous data:
Figure FDA0002244409810000011
in the formula (I), the compound is shown in the specification,
Figure FDA0002244409810000012
for scanning the status information data yiU is the scan state information data yiAnalyzing the standard deviation of the state information data in the time window;
the data anomaly detection module repairs the detected anomalous data, and specifically comprises: if the status information data y is judgediReplacing the abnormal data with a repair value for the abnormal data, and marking;
wherein, the calculation formula of the set restoration value is as follows:
Figure FDA0002244409810000013
wherein y' represents the repair value, max is the maximum value of the state information data in the current data analysis time window, minAnalyzing the minimum value, y, of the state information data within the time window for the current datamedAnalyzing the median of the state information data in the time window for the current data;
the data fusion processing module performs fusion processing on the state information data, and specifically comprises the following steps: regarding the sensors belonging to the same type and the same partition as the same fusion component unit, performing fusion processing on the state information data belonging to the same fusion component unit by taking a time period as a unit, specifically comprising:
(1) taking the state information data belonging to the same fusion composition unit as basic data participating in fusion, calculating the average value of the basic data of each time period corresponding to each sensor (1), and calculating the quantity of the marked state information data in each time period corresponding to each sensor (1);
(2) extracting the average value of the basic data of each sensor in the same time period as the data to be fused to form a data sequence to be fused
Figure FDA0002244409810000021
k is the number of the extracted average values of the basic data, and the noise variance of the sensor (1) corresponding to each data to be fused is obtained;
(3) and calculating the reliability of the sensor (1) corresponding to each data to be fused:
Figure FDA0002244409810000022
in the formula, EiRepresents the sensor (1), E corresponding to the ith data to be fusedlRepresents the sensor (1) corresponding to the first data to be fused,
Figure FDA0002244409810000023
indicating sensor (1) EiThe degree of reliability of the optical waveguide is high,
Figure FDA0002244409810000024
is a sensor (1) EiThe variance of the noise of (a) is,
Figure FDA0002244409810000025
is a sensor (1) ElThe noise variance of (2);
Figure FDA0002244409810000026
in order to ensure that the sensor (1) E is in the time period corresponding to the ith data to be fusediThe number of marked state information data in the collected state information data;
Figure FDA0002244409810000027
in order to ensure that the sensor (1) E is in the time period corresponding to the ith data to be fusediThe number of marked state information data in the collected state information data;
(4) the data sequence to be fused is treated according to the following formula
Figure FDA0002244409810000028
Carrying out fusion treatment:
Figure FDA0002244409810000029
in the formula, y represents the fusion result.
2. The intelligent monitoring system for the numerically-controlled machine tool based on the internet of things as claimed in claim 1, wherein the data collection subsystem comprises a signal adapter for converting sensor signals into corresponding state information data, and the signal adapter is connected with the sensors.
3. The intelligent monitoring system for the numerically-controlled machine tool based on the internet of things as claimed in claim 2, wherein the data collection subsystem further comprises a controller for controlling the collection frequency, and the controller is connected with the sensor.
4. The intelligent monitoring system for the numerically-controlled machine tool based on the internet of things as claimed in claim 1, wherein the user terminal comprises any one or more of an LED display screen, an LCD display screen, a smart phone, a notebook computer and a desktop computer.
5. The intelligent monitoring system of the numerically-controlled machine tool based on the internet of things as claimed in claim 1, wherein the sensor comprises any one or more of a temperature sensor, a vibration sensor, a liquid level sensor, a displacement sensor, a current sensor and a Hall sensor.
6. The intelligent monitoring system for numerically-controlled machine tools based on the internet of things according to any one of claims 1 to 5, wherein when the sensors are deployed, the monitoring area for monitoring the numerically-controlled machine tools is partitioned, different types of sensors are deployed in each partition, the number of the same type of sensors deployed in different partitions is the same, and the data sampling time intervals of the sensors are set to be consistent.
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